Why Do People Dislike Jews – This influence is often used for good—think viral fundraising efforts or defending democratic movements against authoritarian threats—but it can also have the power to strengthen the most vulnerable social relationships. . Racism, sexism, homophobia, misogyny and hate speech are deeply rooted in social media, and criminals have known and taken advantage of it to reach out to the wider world of popular media. .
This report is an attempt to determine the strength of one of these negative thoughts – anti-Semitism – on a social media platform: Twitter – by examining the period from January 29, 2017 to January 28, 2018.
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Often features reports from constituents describing the nature of anti-Semitism on Twitter, including harassment by anti-Semitic trolls. We have published previous research on this phenomenon. Media reports reflect this trend. Experts from the Center on Extremism (COE) wanted to go beyond these reports to understand the problem in detail by examining the tweets for style and context. How many anti-Semitic tweets are posted on Twitter every week? How do you know if tweets are really anti-Semitic? What if some of these tweets purport to carry a satirical or offensive message?
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Using broad-based questionnaires and statistical methods and expert analysis, COE analysts were able to determine approximately 4.2 million anti-Semitic tweets posted and retweeted on Twitter in the one year period noted above. We estimate that the tweets were shared by three million unique handles.
Of course, the 4.2 million tweets are a tiny fraction of the billions of tweets posted on the platform each year. But that doesn’t negate the experiences of Jews who have found Twitter to be a toxic environment. This number goes a long way to show how aggressive and easy it is for many users to pollute our social media environment with hateful and anti-Jewish stereotypes.
This report, along with the random statistical sample of more than 55,000 censored tweets it generated, will also be useful to those developing AI efforts to combat anti-Semitism and bigotry on online.
Are working with Twitter to help them fight anti-racism and other forms of bigotry on their platform, and we know that solving this problem is difficult. We’re proud to join Twitter’s Safety and Security Council and work with Twitter as a member of our Problem Solving Lab to explore automated ways to combat hate speech and harassment. We’ve already seen the company make progress on these issues and show leadership across social media.
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However, despite recent advances, sentiment still exists on social media platforms such as Twitter. It reduces speech and bitterness in public discourse for all. Even a few tweets showing anti-Semitism is too much, and every campaign that harbors such hatred must make sure that it uses all means to correct the situation, even if it aims to balancing legitimate concerns about not restricting the expression of freedom. . For this reason, this report contains not only an overview of our findings, but a series of recommendations that Twitter should consider in an attempt to solve problems and improve its performance.
We look forward to continuing to work with Twitter – and other platforms that seek help – to ensure that these environments are safe places for all users, regardless of their faith, race or other neutral attributes.
As a result of a pilot research project, the Anti-Defamation League was able to determine that between January 29, 2017 and January 28, 2018, approximately 4.2 million English-language anti-Semitic tweets were shared. The analysis showed that during the seven days selected, the number of tweets expressing anti-Semitic sentiments went from a low of 36,800 in week 26 (July 23-29) to peak of 181,700 in week 45 (03- 09 December). The average number of anti-Semitic tweets over the entire 52 weeks analyzed was 81,400.
The present findings are based on a complex logical question designed to identify the language often used by anti-Semites. The study was written to cover manifestations of anti-Semitism, including traditional anti-Semitic practices; code words and symbols are sometimes used in an anti-Semitic sense; and subtle references to anti-Semitic conspiracy theories.
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Experts from the Center on Extremism reviewed a large sample of tweets received by this application on a weekly basis. The scores are designed to determine the percentage of tweets that do not purport to express anti-Semitic sentiments or promote anti-Semitic conspiracy theories. Of particular importance are tweets that use or mention anti-Semitic language to criticize or use anti-Semitic language. In these cases, analyzing the context of the thread (and associated videos and images) is very important. In some cases, to determine opinions, the information provided by the tweeter in the “biography” field was also used. If experts were not sure that a tweet was anti-Semitic, it was marked as having no anti-Semitic intent. For each time, a large number of tweets were evaluated to obtain an error of 3%.
The resulting percentage of anti-Semitic tweets in the representative sample is then returned to the total population of tweets retrieved by the query at that time. This led to a number of anti-Semitic tweets being revealed in the findings.
This project is the second attempt to determine the extent of anti-Semitism on Twitter. An October 2016 report used keywords related to anti-Semitism to estimate the total number of tweets that may contain anti-Semitic content and advise reporters. The current report advances the methodology by going beyond a simple keyword search and estimating the number of facts of true anti-Semitic sentiment. The current report expands the scope of the first study looking at anti-Semitism in all English-language tweets.
A third project, the Internet Hate Index, developed by the Institute for Technology and Society, tried to use artificial intelligence and machine learning to detect the nature of hate speech on individual Reddit forums. The current campaign focuses exclusively on anti-Semitism, including hard-to-detect anti-Semitic conspiracy theories, created and implemented by human experts without automation or machine learning. we hope that the results of tweets tagged with anti-Semitism will be useful for training machine learning algorithms to detect anti-Semitism.
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The current report is based on a master logic question developed by experts at the Center on Extremism. Anti-Semitic content is requested in the following categories:
Current media includes criticism of Israel or Zionism when such criticism uses classic anti-Semitic language or ideologies, while promoting hate speech. to many Jews. Public criticism of Israel and its policies is not considered anti-Semitism. [See below — When anti-Zionism is anti-Semitic.]
The current study covers all aspects of tweets that purport to carry anti-Semitic content, including retweets. However, cases in which anti-Semitic tweets were also posted against them were excluded from the study, as described above.
Because the request is based on Twitter data obtained at the beginning of January 2018, it does not include the number of anti-Semitic tweets that have been deleted by their owners, from accounts that have been closed by Twitter for violate its terms of service. As a result, the actual number of anti-Semitic tweets is undoubtedly higher than the number estimated in this study.
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In addition, the data for this study was released before the so-called “Twitter purge” at the end of February 2018, when Twitter deleted thousands of accounts related to automatic tires. Some of the anti-Semitic tweets were posted by those bots, so a recent Twitter search found fewer anti-Semitic tweets than reported in this report.
The logical question is based on text, so tweets containing anti-Semitic images without anti-Semitic text will not be included. This is another reason why we believe that the actual number of anti-Semitic tweets is higher than assumed in this study.
The question of this research was designed to be too broad to return all results as anti-Semitic. That’s why the following review by anthropologists is so important (that is, to analyze non-anti-Semitic tweets that we knew would come in). From January 29, 2017 to January 31, 2018, our query collected nearly nineteen million tweets, with weekly numbers ranging from 183,000 (week 30: July 23-29) up at one million tweets (week 33: August 13-19) .
We send a random statistical sample of more than 1,000 tweets per week (more than 55,000 in a year) to manual analysis for the presence of anti-Semitic ideas, the spread of anti-Semitic ideas anti-Semitic. . Our sample sizes allowed for a margin of error of three percent. 4.2 million anti-Semitic tweets were found, with weekly numbers ranging from a low of 36,800 in week 26 (23-29 July) to a high of 181,700 in week 45 (03-09 December).
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